A Nonparametric Test for Interval-Censored Failure Time Data with Unequal Censoring |
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Authors: | Chao Zhu Kam C Yuen Xingqiu Zhao |
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Institution: | 1. Bristol-Myers Squibb Co. , Wallingford, Connecticut, USA;2. Department of Statistics &3. Actuarial Science , The University of Hong Kong , Hong Kong;4. Department of Mathematics &5. Statistics , McMaster University Hamilton Hall , Hamilton, Ontario, Canada |
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Abstract: | This article considers nonparametric comparison of survival functions, one of the most commonly required task in survival studies. For this, several test procedures have been proposed for interval-censored failure time data in which distributions of censoring intervals are identical among different treatment groups. Sometimes the distributions may depend on treatments and thus not be the same. A class of test statistics is proposed for situations where the distributions may be different for subjects in different treatment groups. The asymptotic normality of the test statistics is established and the test procedure is evaluated by simulations, which suggest that it works well for practical situations. An illustrative example is provided. |
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Keywords: | Interval-censored data Linear functional Two sample comparison Unequal censoring |
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